DNA methylation is a chemical modification of cytosine bases that is pivotal for gene regulation,cellular specification and cancer development. Here, we describe an R package, methylKit, thatrapidly analyzes genome-wide cytosine epigenetic profiles from high-throughput methylation andhydroxymethylation sequencing experiments. methylKit includes functions for clustering, samplequality visualization, differential methylation analysis and annotation features, thus automatingand simplifying many of the steps for discerning statistically significant bases or regions of DNAmethylation. Finally, we demonstrate methylKit on breast cancer data, in which we find statisticallysignificant regions of differential methylation and stratify tumor subtypes. methylKit is availableat http://code.google.com/p/methylkit.

What to expect after a year in space: Space is the final frontier for understanding how extreme environments affect human physiology. Following twin astronauts, one of which spent a year-long mission on the International Space Station, Garrett-Bakelman et al. examined molecular and physiological traits that may be affected by time in space (see the Perspective by Löbrich and Jeggo). Sequencing the components of whole blood revealed that the length of telomeres, which is important to maintain in dividing cells and may be related to human aging, changed substantially during space flight and again upon return to Earth. Coupled with changes in DNA methylation in immune cells and cardiovascular and cognitive effects, this study provides a basis to assess the hazards of long-term space habitation. Science , this issue p. eaau8650 ; see also p. 127

A large number of computational methods have been developed for analyzing differential gene expression in RNA-seq data. We describe a comprehensive evaluation of common methods using the SEQC benchmark dataset and ENCODE data. We consider a number of key features, including normalization, accuracy of differential expression detection and differential expression analysis when one condition has no detectable expression. We find significant differences among the methods, but note that array-based methods adapted to RNA-seq data perform comparably to methods designed for RNA-seq. Our results demonstrate that increasing the number of replicate samples significantly improves detection power over increased sequencing depth.

The epitranscriptomics field has undergone an enormous expansion in the last few years; however, a major limitation is the lack of generic methods to map RNA modifications transcriptome-wide. Here, we show that using direct RNA sequencing, N⁶-methyladenosine (m⁶A) RNA modifications can be detected with high accuracy, in the form of systematic errors and decreased base-calling qualities. Specifically, we find that our algorithm, trained with m⁶A-modified and unmodified synthetic sequences, can predict m⁶A RNA modifications with ~90% accuracy. We then extend our findings to yeast data sets, finding that our method can identify m⁶A RNA modifications in vivo with an accuracy of 87%. Moreover, we further validate our method by showing that these ‘errors’ are typically not observed in yeast ime4-knockout strains, which lack m⁶A modifications. Our results open avenues to investigate the biological roles of RNA modifications in their native RNA context.

The RNA modification N6-methyladenosine (m6A) post-transcriptionally regulates RNA function. The cellular machinery that controls m6A includes methyltransferases and demethylases that add or remove this modification, as well as m6A-binding YTHDF proteins that promote the translation or degradation of m6A-modified mRNA. We demonstrate that m6A modulates infection by hepatitis C virus (HCV). Depletion of m6A methyltransferases or an m6A demethylase, respectively, increases or decreases infectious HCV particle production. During HCV infection, YTHDF proteins relocalize to lipid droplets, sites of viral assembly, and their depletion increases infectious viral particles. We further mapped m6A sites across the HCV genome and determined that inactivating m6A in one viral genomic region increases viral titer without affecting RNA replication. Additional mapping of m6A on the RNA genomes of other Flaviviridae, including dengue, Zika, yellow fever, and West Nile virus, identifies conserved regions modified by m6A. Altogether, this work identifies m6A as a conserved regulatory mark across Flaviviridae genomes.